A Comprehensive Prognostic Model for Colorectal Cancer Liver Metastasis Recurrence After Neoadjuvant Chemotherapy - Zhou, Zhenyuan; Han, Xin; Sun, Diandian; Liang, Zhiying; Wu, Wei; Ju, Haixing (Frontiers in Oncology, 2022)
Background: For patients with colorectal liver metastases (CRLMs), it is important to stratify patients according to the risk of recurrence. This study aimed to validate the predictive value of some clinical, imaging and pathology biomarkers and develop an operational prognostic model for CRLMs patients with neoadjuvant chemotherapy (NACT) before the liver resection. Methods: CRLMs patients accompanied with primary lesion and liver metastases lesion resection were enrolled into this study. A nomogram based on independent risk factors was identified by Kaplan-Meier analysis and multivariate Cox proportional hazard analysis. The predictive ability was evaluated by receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Calibration plot were also used to explore the consistency between prediction and reality. Results: A total of 118 patients were enrolled into the study. Multivariable Cox analysis found that histopathological growth patterns (HGPs) (HR = 2.130), radiology response (stable disease vs. partial response, HR = 2.207; progressive disease vs. partial response, HR = 3.824), lymph node status (HR = 1.442) and age (HR = 0.576) were independent risk factors for disease-free survival (DFS) (p < 0.05). Corresponding nomogram was constructed based on above factors, demonstrating that scores ranging from 5-11 presented better prognosis than the scores of 0-4 (median DFS = 14.3 vs. 4.9 months, p < 0.0001). The area under ROC curves of the model for 1-, 2- and 3-year DFS were 0.754, 0.705 and 0.666, respectively; and DCA confirmed that the risk model showed more clinical benefits than clinical risk score. Calibration plot for the probability of DFS at 1- or 3-year verified an optimal agreement between prediction and actual observation. In the course of our research, compared with pure NACT, a higher proportion of desmoplastic HGP (dHGP) was detected in patients treated with NACT plus cetuximab (p = 0.030) and use of cetuximab was an independent factor for decreased replacement HGP (rHGP) and increased dHGP (p = 0.049). Conclusion: Our model is concise, comprehensive and high-efficiency, which may contribute to better predicting the prognosis of CRLMs patients with NACT before the liver resection. In addition, we observed an unbalanced distribution of HGPs as well.